Application of mass spectrometry-based proteomics for biomarker discovery in neurological disorders

Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Quantitative proteomic approaches have already been applied to investigate various neurological disorders, especially in the context of identifying biomarkers from cerebrospinal fluid and serum. This review highlights the scope of different applications of quantitative proteomics in understanding neurological disorders with special emphasis on biomarker discovery.


Introduction
Neurological disorders are a major cause of physical disability and mortality worldwide. However, there is still a paucity of studies investigating the molecular mechanisms of disease progression and biomarkers of diagnostic and prognostic value. Mass spectrometrybased proteomic profiling has been employed in investigating several neurological diseases [1][2][3] and to identify diagnostic biomarkers in psychosis, Guillain-Barré syndrome, multiple sclerosis and Alzheimer's disease. [4][5][6][7][8][9] Proteome is the entire complement of proteins expressed by the genome at any given time in a cell, tissue or an organism, while proteomics deals with the characterizing features of gene products such as posttranslational modifi cations, protein isoforms, subcellular localization, protein-protein interactions and tissue expression. [10,11] As proteins are the functional molecules in cells, measurement of the diff erential expression of proteins could indicate disease-specifi c changes in tissues or organs. In vivo labeling using the SILAC method or in vitro labeling approaches such as isotope-coded affi nity tagging allows simultaneous identifi cation of proteins and quantitation of their abundance levels. [12,14] A number of studies have shown that quantitative proteomics is a promising approach for discovery of potential biomarkers for early detection and to understand drug responses and molecular pathogenesis. [15] Candidate biomarkers identified using proteomic profiling of serum and cerebrospinal fluid (CSF) could be used for diagnosis, prognosis and determining therapeutic response to diff erent treatment modalities. [1,4,16,17] The majority of published studies by proteomic approaches to study neurological disorders have used two-dimensional gel electrophoresis (2-D PAGE), which has a number of limitations. [18][19] Quantitative mass spectrometry approach off ers an att ractive option to investigate disease-specifi c changes with high-degree of specifi city and sensitivity. This brief review will present diff erent types of quantitative proteomic approaches and their applications in neurological disorders.

Trascriptomics versus proteomics
Genetic variability is plausible for different disease phenotypes; this could be at the level of alterations at transcription, translation and posttranslational modifi cation of gene expression. DNA microarrays allow cataloging of gene expression under diff erent conditions. Blalock et al. carried out a transcriptomic analysis of incipient Alzheimer's disease (AD) using DNA microarrays. [20] They studied gene expression profi le in hippocampus of 9 control and 22 AD subjects of varying severity. The study revealed activation of growth and diff erentiation pathways, and downregulation of protein transport machinery. In the DNA microarray approach, the mRNAs are labeled with fl uorescent dyes followed by hybridization with DNA probes immobilized in an array format at a very high density. Relative fl uorescence between samples provides a measure of the relative abundance of mRNAs present in the samples. Table 1 outlines some of the considerations for sample collection and handling for mRNA and protein-based biomarker discovery. DNA microarrays provide readout of the transcriptional activity of genes but do not provide data on protein expression or post-translational modifi cations of proteins in the samples. Proteomic approaches, especially those involving mass spectrometry, provide data on protein expression as well as post-translational modifi cations in diff erent disease conditions, which could lead to the discovery of biomarkers. The biomarker discovery pipeline using proteomics entails sample extraction, diff erential labeling of samples, fractionation, tandem mass spectrometry (MS/MS) and data analysis. To identify biomarkers in traumatic brain injury patients, Hergenroeder et al. used pooled sera from patients and labeled the samples using isobaric tags followed by liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. [21] Mass spectrometry for proteomic analysis Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) is widely used today for characterization of biological samples with high level of sensitivity and specifi city. Diff erent mass spectrometric methods are available for proteomic profiling and identification of biomarkers. One of the platforms is surface-enhanced laser desorption-ionization (SELDI), which has been used to obtain disease specifi c proteomic patterns. [22] However, in this approach, only mass spectrometry peak patterns are obtained and the exact identity of the peaks are not determined (i.e. the proteins are not identifi ed in this type of mass spectrometry). [23] Other platforms such as tandem mass spectrometry permit actual identifi cation of amino acid sequences of peptides and are preferable to SELDI for detecting biomarkers.
There are several labeling approaches for performing mass spectrometry-based quantitative proteomics analysis. These include labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC) [12] and isobaric tags for relative and absolute quantitation (iTRAQ), [24] cysteine labeling using isotopecoded affi nity tags, [14] labeling with isotopically labeled acrylamide and C-terminal labeling using 18 O-labeled water. [25] In a SILAC experiment, cells representing different biological conditions are grown in media supplemented with either "light" or "heavy" isotope form of amino acids. In this method, labeled amino acids are metabolically incorporated into all peptides and subsequent pooling of diff erentially labeled samples in equal ratios provides quantifi cation of peptides from each sample. This quantifi cation of proteins is based on the relative intensities of corresponding diff erentially labeled peptides. SILAC has been used to study signaling in several systems including the phosphorylation dynamics of ion channels and to evaluate the brain derived neurotrophic factor (BDNF) induced change in neuronal phosphotyrosine proteome. [26,27] However, the disadvantages of this method is that, it cannot be used for tissues or body fl uids and might require further validation as the experiments are carried out in cell lines. Park et al. used this method to quantitate the phosphorylation of Kv2.1 protein, which was transfected to HEK293 cell lines and activated by ionomycin to study calcineurin dependent dephosphorylation. [26] It has also been used to identify BDNF-induced proteins, which

Sample storage
Tissue should be either fl ash frozen or immersed in Tissues: Tissues should be snap frozen in liquid nitrogen and transport a tissue stabilization solution such as RNAlater. and stored at -80°C until used Archived frozen tissue should be quickly disrupted CSF: Specimens should be centrifuged immediately at or solutions such as RNAlater-ICE should be used 2000g for 10 min at 4°C to remove cells and other debris. for thawing purposes. Multiple freeze/thaw cycles Supernatants should be snap frozen immediately and stored should be avoided. Immediate processing will at −80°C in aliquots. minimize RNA degradation Serum/plasma: The blood samples should be centrifuged at 1300 g at 4°C and stored at −80°C in aliquots.

Quality control
Quality of the samples should be judged by The sample integrity can be assessed by SDS-PAGE. RNA purity (A 260 /A 280 ) and integrity (18S:28S ratio).
includes tyrosine kinase receptor B, hepatocyte growth factorregulated tyrosine kinase substrate and signal transducing adaptor molecule. All these proteins are known to control the molecular traffi cking of receptor tyrosine kinases. [27] 2D-PAGE is widely used for protein separation for comparative proteomic profi ling [ Figure 1]. DIGE is a vital part of the 2D-PAGE for protein quantitation, [28] in spite of its limitations (the biggest limitation is that only the most abundant proteins can be analyzed). [29] In DIGE, diff erent samples are labeled with diff erent fl uorescent dyes prior to separation, facilitating analysis of diversity in protein abundance between samples. DIGE separates protein samples into spots, which could be subsequently identifi ed by tandem mass spectrometry. Soft ware is required to extract quantitative information; additional normalization [30] and stringent statistical tests are oft en required for analyzing the data. [31] The data obtained from the 2D gel analysis should be validated using immunohistochemical labeling or enzyme assays, as the protein spots in 2-D gel can co-migrate leading to confusion in the identity of proteins. Some of the neurological disease biomarkers revealed by DIGE approach are listed in Table 2. Gao et al. performed DIGE to analyze the proteomic profi le of cerebrospinal fl uid in traumatic brain injury in infants, which is one of the common causes of mortality in infancy. The study identifi ed candidate biomarkers such as prostaglandin D2 synthase and cystatin C, further confi rmed by Western blot. [19] Maternal serum profiling was performed to identify candidate biomarkers for Down syndrome using 2D-DIGE coupled to MALDI-TOF MS analysis. [18] This study proposed diff erential expression of molecules such as afamin, alpha-1-microglobulin, apolipoprotein E and ceruloplasmin in the maternal serum.
iTRAQ reagents are a set of isobaric tags that bind to primary amines by covalent bond leading to the labeling of peptides. Measuring the relative intensity of these reporter ions in MS/MS spectra allows the relative quantitation of the proteins in samples. Choe et al. used 8-plex iTRAQ quantitation of proteins in cerebrospinal fl uid of the patients with Alzheimer's disease. The study observed a decrease in some proteins, which include albumin, clusterin and hemopoxin. [32] The proteins with the increased expression include apolipoprotein E and cystatin C. Since eight types of the reporter molecules are now available, this method allows multiplexing of up to eight sets of samples in a single mass spectrometry experiment. Table 2 provides the list of some of proteomic studies in neurological diseases. Hergenroeder et al. investigated for candidate serum biomarkers for brain injury using iTRAQ method coupled with LC-MS/MS. The study identifi ed serum amyloid A, C-reactive protein and retinol binding protein 4 and these candidate biomarkers were verified by enzyme-linked immunosorbent assay (ELISA) in an independent set of serum samples from cases of traumatic brain injury and healthy volunteers. [21] Biomarker discovery in CSF and serumpromises and challenges One of the major goals of diagnostic biomarker discovery is development of a simple and accurate blood test for early diagnosis of disease. Human serum/plasma remains the easily accessible and commonly used clinical sample for proteomics applications. Human plasma has been described as a circulating representation of all body tissues in both physiological and pathological processes. [33] This is because serum/plasma is in direct or indirect contact with the cells or tissues in the body hence may contain specifi c biomarkers in soluble phase for easy identifi cation. However, the advantages of plasma as one of the easy to obtain sample is counter balanced by analytical challenges posed by the complexity of the plasma proteome and also the genetic diversity of human population. Sample preservation for proteomics analysis also plays a crucial role in outcome of quantitation.
Pre-analytical variables have a potential influence For serum analysis, the sample should be allowed to clot for 30-60 min before processing to minimize the diff erences arising from the eff ects of coagulation. [34] Plasma preparation for proteomic analysis is carried out by treating the samples with anticoagulants, which also have inherent advantages and disadvantages. [35] The choice of the anticoagulants, such as EDTA, citrate and heparin, is based on the downstream applications of the sample. Other pre-analytical variables such as centrifugation (speed, time, and temperature) are likely to have signifi cant eff ect on sample stability. The use of protein inhibitor cocktails for storage of body fl uids has detectable benefi ts in stabilizing the proteins. Another factor that affects the proteomic analysis is storage temperature. [35] The samples should be stored frozen and repeated freeze/thaw cycles should be avoided and samples should be subjected to uniform protocol of handling for reproducible quantitative analysis.
To optimize the sensitivity limits of biomarker discovery using mass spectrometry, enrichment of less abundant proteins in serum (proteins present in subtle quantities and yet important in physiology) is critical -this might require the depletion of the abundant proteins such as albumin, immunoglobulins, transferrin and macroglobulins. Depletion of these abundant proteins can be carried out by affi nity chromatography methods involving multiple protein depletion in a single separation step. This increases the chances of detecting candidate biomarkers, which are likely to be present in low abundance. Figure 2 demonstrates the eff ect of depletion of major six proteins from serum using a multiple affi nity column (Agilent, Multiple Affi nity Removal LC Column). Ramstrom et al. reported a method for removal of "brain-specific abundant protein" in addition to common serum proteins. [36] The damage to the blood-brain barrier (BBB), a known event in many of the neurological diseases, may enhance movement and mixing of proteins between the brain interstitial space and blood; thus serum can be considered as an appropriate sample to study. [37] However, since the CSF provides a direct insight into the neurological microenvironment, it should be considered a preferred body fl uid for proteomic analysis for biomarker discovery and diagnosis of neurological diseases. [9] In pathological states, the cells in the brain are likely to shed the altered proteins into CSF and thus be available for analysis. [38] Apart from this, the high amount of immunoglobulins in many neurological diseases also indicates the need for specifi c isolation and fractionation methods. [10,39] Using multiple affi nity purifi cation columns, majority of the abundant proteins from serum and CSF can be depleted before the proteomics analysis. [40] Mass spectrometry to identify biomarkers for early diagnosis of neurological diseases Many neurological diseases are analyzed for identifi cation of candidate biomarkers by different proteomic approaches. Here, we provide an overview of published studies in which proteomic profiling was used to understand various neurological disorders. Table 3 lists some of the applications of mass spectrometry-based proteomics in diff erent neurological diseases.
Psychosis: Proteomic profi ling of cerebrospinal fl uid from patients with fi rst onset of psychosis, using SELDI mass spectrometry, identifi ed increased VGF-derived peptide in cases of schizophrenia compared to healthy volunteers. [5] Further validation of VGF-derived peptide in an independent set of psychosis patients with schizophrenia and without schizophrenia could be useful to prove that the proteins identifi ed are really schizophrenia specific. Craddock et al. profiled the proteome of T cell lysates from schizophrenia patients, and the study identifi ed alpha defensin as a candidate biomarker, which was also verifi ed in an independent set of patients of schizophrenia, their family members and healthy volunteers using ELISA. [1] Neurodegenerative diseases: Sultana et al. analyzed hippocampus proteome of Alzheimer 's disease patients. [41] The differentially upregulated proteins include enolase, ubiquitin carboxyl terminal hydrolase L-1 and triosephosphate isomerase. Simonsen et al. used cerebrospinal fluid to detect candidate biomarkers, which are capable to diff erentiate between patients with stable mild cognitive impairment (MCI) and those who will progress to Alzheimer's disease (AD). [42] The study identifi ed proteins such as ubiquitin and phosphorylated C-terminal fragment of osteopontin as potential biomarkers. By quantitative proteomic analysis of frontal cortex of parkinsonism-dementia complex cases using iTRAQ labeling, alpha synuclein is identified as a candidate biomarker. [43] Lee et al. performed peptide mass fi nger printing to identify candidates for Alzheimer's disease   [44] and found fi brinogen gamma-A chain precursor protein to be upregulated with the progression of the disease. Profi ling of plasma proteome in Huntington's disease revealed over expression of identifi ed clusterin and IL-6 with respect to controls. [45] Likewise, validation by ELISA experiments on an independent set of patient samples confi rmed that clusterin and IL-6 are increased in plasma. Stoop et al. used quantitative mass spectrometry to profi le the cerebrospinal fl uid proteome of multiple sclerosis patients where a panel of candidate biomarkers were identified such as chromogranin A, clusterin, complement C3 and complement C4B. [8] Neurotrauma: Haqqani et al. used isotope-coded affi nity tags (ICAT) followed by tandem mass spectrometry to perform serum proteomic profi ling of pediatric patients of traumatic brain injury, where serum samples were depleted of high abundant molecules such as albumin and immunoglobulin. [46] The proposed candidate biomarkers included ornithine carbamoyl transferase, IL-1R like precursor and Toll like receptor 9 like precursor. Conti et al. analyzed CSF from cases of severe traumatic brain injury using 2D-PAGE combined with mass spectrometry. [47] In this study, proteins such as alpha 1 antitrypsin, haptoglobin 1 alpha1, alpha2, and beta belonging to the acute phase response were found over expressed. Interestingly, two other proteins, identifi ed as proteolytic degradation products of the carboxylterminal portion of the fi brinogen beta, were present in the CSF of individuals with traumatic brain injury. These candidate proteins could be indicators of post traumatic infl ammatory process as well as the fi brinolysis in the microenvironment of the tissue injury.
Neoplasms of the central nervous system: Roy et al. used diff erential quantitation without isotopic labeling coupled to LC-MS/MS to profile the proteome of cerebrospinal fl uid from CNS-lymphoma patients. [7] Here, the study elucidated candidate biomarkers such as antithrombin III and alpha-1-acid glycoprotein.protein.
Additionally, the expression of antithrombin III was immunohistochemically validated in CNS lymphoma tissues and also found in cerebrospinal fl uid by ELISA. For elucidating therapeutic biomarkers of angiogenesis in glioma, Mustafa et al. explored the proteome of glioma tumor vessels, which was microdissected by Laser Capture Microscopy. [2] The study employed nano-LC fractionation and MALDI-FTMS to identify the potential biomarkers including fi bronectin and colligin 2. Further, fi bronectin and colligin 2 were validated on glioma tissue sections using specifi c antibodies. Park et al. used 2D-PAGE and MALDI-TOF mass spectrometry approach to analyze the proteome of anaplastic oligodendroglioma tissues, where peroxiredoxin 6 was identifi ed to be overexpressed and later validated by Western blot and immunohistochemistry. [48] Khwaja et al. identifi ed potential biomarkers in cerebrospinal fl uid for central nervous system malignancies using MALDI analysis. [49] The study identifi ed cystatin and carbonic anhydrase, which needs be further validated for its sensitivity and specifi city.
HIV-associated cognitive impairment: Cerebrospinal fl uids from HIV-1 seropositive patients were studied using proteomics platform consisting of SELDI-TOF, reverse phase high performance liquid chromatography (RP-HPLC) sample fractionation, SDS-PAGE, and LC-MS/MS. [50] The study identified proteins such as soluble superoxide dismutase (SOD1), migration inhibitory factor (MIF) -related protein 14

Mass spectrometry for investigating mechanisms of neurological diseases
Proteomic analysis could help to understand complex protein-protein interactions and molecular pathways in physiological functions of the nervous system. Husi et al. characterized N-methyl-D-aspartate receptors (NMDAR) multiprotein complex by immunoaffi nity chromatography followed by LC-MS. [51] NMDAR multiprotein complexes (NRC) comprise 77 different proteins, including receptors, adaptors, signaling molecules, cytoskeletal and novel proteins. NRC mediates long-lasting changes in synapse strength via downstream signaling pathways. Genetic or pharmacological interference with 15 NMDAR multiprotein complex proteins impairs learning, while with 22 proteins, it alters synaptic plasticity in rodents. Here, mutations in three human genes (NF1, Rsk-2, L1) are associated with learning impairments, indicating that the NRC also participates in human cognition. A study of synaptic multiprotein complexes associated with the 5-HT (2C) receptor has also been carried out by affinity chromatography and 2D-PAGE followed my MALDI-TOF mass spectrometry. [3] This approach identifi ed 15 proteins that interact with the C-terminal tail of the 5-hydroxytryptamine 2C (5-HT 2C ) receptor, a G-protein-coupled receptor. These proteins include several synaptic multidomain proteins containing one or several PDZ domains (PSD95 and the proteins of the tripartite complex Veli3-CASK-Mint1), proteins of the actin/spectrin cytoskeleton and signaling proteins. Identifi cation of these proteins could help in understanding the signaling pathways associated with 5-HT 2C receptors in neurons. Activation of 5-HT 2C receptors exerts a phasic and tonic inhibition of the mesocorticolimbic dopamine function. This suggests that 5-HT 2C receptor antagonists may be useful for the treatment of negative schizophrenia symptoms.
A SELDI-based approach has been used for the development of potential markers for Stiff person syndrome (SPS). [52] This approach identified downregulation of GABA-A-receptor-associated protein (GABARAP), which enables assembly of GABAA-receptor into the plasma membrane. The level of this protein was found to be inversely correlated with the autoantibodies raised against GABA-A-receptor-associated protein in the sera of patients, leading to the conclusion that GABARAP could be a new potential auto antigen in SPS, which could be damaging GABAergic pathway, pathogenetically involved in disease evolution. Analysis of phosphorylation in Kv1.2-containing Kv channels by SILAC labeling identified in vivo phosphoserine (pS) sites at pS434, pS440 and pS441. [53] The study suggests that stimuli that alter activity levels of Ser-directed protein kinases and phosphatases may affect expression levels of Kv1.2-containing Kv channels through an effects on C-terminal of Kv1.2 phosphorylation sites and biosynthetic intracellular trafficking. Changes in the Kv channel phosphorylation state mediate changes in electrical excitability in response to altered synaptic activity and thus neuromodulation leading to the susceptibility to seizure due to the reduced trafficking. Mass spectrometric analysis of isolated di-heteromeric receptors identified a novel NMDAR interactor and collapsin response mediator protein 2 (CRMP2) that preferentially associates with NR2Bcontaining di-heteromeric NMDARs. [54]

Future perspectives
Biomarkers are essential for understanding the pathogenesis and development of diagnostic and therapeutic tools in complex neurological disorders. With the recent advances in mass spectrometry and labeling methods, quantitative proteomics holds immense potential for biomarker discovery of neurological disorders. Subproteome analysis by means of depletion of abundant proteins, lectin affi nity fractionation, and subcellular fractionation may facilitate the identifi cation of vital molecules by reducing the complexity. With a panel of candidate diagnostic biomarkers, validation can be performed on larger patient population using proteomic techniques such as bead-based assays. High throughput proteomic studies involved in global analysis of neurological disorders form a valuable repository of data and can be useful in translating eff ectively the discoveries into clinical practice. Neuroproteomics has an added advantage of correlating phenotypic changes Venugopal et al.: Proteomics for biomarker discovery in neurological disorders such as altered cognition and learning with proteomic changes. In conclusion, mass spectrometry-based proteomics off ers a promising platform to understand pathogenesis of disease and for discovery of biomarkers for early detection. A close interaction between the clinician and the specialist basic scientist will unravel new avenues of early diagnosis and evolving therapeutic strategies.